{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Replication file for 'The Intertemporal Keynesian Cross'\n",
    "### Part II: fiscal policy in the IKC environment (section 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Adrien Auclert, Matthew Rognlie, Ludwig Straub\n",
    "\n",
    "April 2024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jacobian_manipulation as jac\n",
    "import calibration\n",
    "import models_analytical, models_heterogeneous\n",
    "import sec5_plots as plots\n",
    "\n",
    "opts = {'texfig': True, 'savefig': True} # flags for plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preliminary: calculate M and A matrices for all models\n",
    "First, we need to load the saved `params` dictionary from our calibration in `main_sec34.ipynb`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('solved_params.json', 'r') as f:\n",
    "    params = json.load(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For analytical models, this data is enough to calculate the M and A matrices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = 500\n",
    "r = calibration.r\n",
    "Ms, As = models_analytical.MA_all(params, r, T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For heterogeneous-agent models, we will load the household blocks and calculated the steady states, then calculate the matrices. This is almost immediate except for the HA-two model, where it may take 15-60 seconds:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "hh_het, ss_het = models_heterogeneous.get_all(params)\n",
    "for m in ss_het:\n",
    "    J = hh_het[m].jacobian(ss_het[m], inputs=['Z'], outputs=['C', 'A'], T=T)\n",
    "    Ms[m], As[m] = J['C', 'Z'], J['A', 'Z']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculate fiscal multipliers\n",
    "\n",
    "#### Calculating $\\mathcal{M}$ (`curlyM`)\n",
    "First, we need to calculate the $\\mathcal{M}$, or `curlyM`, operator for each model. Recall that equation (16) states that the solution to the IKC is\n",
    "$$\n",
    "\\mathcal{M} \\equiv (\\mathbf{K}(\\mathbf{I}-\\mathbf{M}))^{-1}\\mathbf{K} = \\mathbf{A}^{-1}\\mathbf{K}\n",
    "$$\n",
    "To avoid problems arising from the truncation, we will directly use $\\mathbf{A}$ rather than calculating $\\mathbf{K}(\\mathbf{I}-\\mathbf{M})$. (ADD MORE BELOW ON DIFFERENT WAYS TO SOLVE.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "K = jac.Kmat(r, T)\n",
    "curlyMs = {m: np.linalg.solve(As[m], K) for m in As}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One annoying detail: note that as an infinite-dimensional object, $\\mathbf{A}$ is actually not invertible for the RA and TA models, so that this formula does not directly apply for them. As observed in section 5 of the paper, this corresponds to multiplicity in the RA and TA models, which takes the form of a permanent level shift in $dY_t$. This multiplicity goes away once we make the additional assumption that $dY_t\\rightarrow 0$ (assuming $dG_t,dT_t\\rightarrow 0$).\n",
    "\n",
    "In practice, we can select the $dY_t\\rightarrow 0$ equilibrium by multiplying $\\mathbf{M}$ on the left by an operator that subtracts the last entry (which should be zero) from all others. This is equivalent to subtracting the last row from all other rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "curlyMs['RA'] -= curlyMs['RA'][-1]\n",
    "curlyMs['TA'] -= curlyMs['TA'][-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Calculating fiscal multipliers for main exercise\n",
    "Our main exercise will be an AR(1) shock to spending with persistence $\\rho_G$, for various persistences $\\rho_B$ of debt. We'll calculate the multipliers on impact, cumulatively, and also (though not in our graphs) over a 5-year horizon."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "dG = calibration.rhoG ** np.arange(T)\n",
    "NrhoB = 20\n",
    "rhoBs = np.linspace(0, calibration.rhoB, NrhoB)\n",
    "mult_impact, mult_5yr, mult_cumul = {}, {}, {}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let's calculate the implied tax plan $dT$ for each $\\rho_B$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from aux_fiscal import Bplan, Tplan, compute_multipliers\n",
    "dBs = [Bplan(dG, rho_B) for rho_B in rhoBs]\n",
    "dTs = [Tplan(dG, dB, 1+r) for dB in dBs] # TODO: change TPlan to take r as input instead"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, for each model, calculate $dY$ and multipliers for each $\\rho_B$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "dYs = {}\n",
    "for m in curlyMs:\n",
    "    m_impact, m_5yr, m_cumul, dYs[m] = np.empty(NrhoB), np.empty(NrhoB), np.empty(NrhoB), {}\n",
    "    \n",
    "    # iterate over rhoBs and the associated dT plan\n",
    "    for i, (rhoB, dT) in enumerate(zip(rhoBs, dTs)):\n",
    "        # calculate dY using equation (16), store implied multipliers\n",
    "        dYs[m][i] = curlyMs[m] @ (dG - Ms[m] @ dT) \n",
    "        m_impact[i], m_5yr[i], m_cumul[i] = compute_multipliers(dYs[m][i], dG, r)\n",
    "\n",
    "    mult_impact[m], mult_5yr[m], mult_cumul[m] = m_impact, m_5yr, m_cumul"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure 5\n",
    "Plotting the resulting fiscal multipliers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figure5(rhoBs, mult_impact, mult_cumul, **opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure E.2\n",
    "Now plotting multipliers for all models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9ERERjrpiY2OJi4sjKyuLkJAQ0tPTK9hJQkJC2LBhg6eXLQi1ZuKcORxZvpzAdu181mbnzvCHPxj/r3khi4JzBQCMuH+Ez2SoKaIkgL594dprK88zYkTZzxZL1WVc4Vymb1/Py9cEu/0hLi7OkWZ/eNtsNocCsI8w7CQlJbmdEnJWGuWVSPnzmZmZnD592jFF1aFDB2JiYoiIqLCQQhC8TsvOnbnMnPb0NcWFxaz/z3oAOg7qSP+b+teLHJ4gSoKaTfuMGFFxKqk61KRMbZk/fz6ZmZkV0pVSZaZ8kpKSSEpKKpMnNTXVMRJxfvDbbDaXoxZX2MvZp7sE4VLhyy+N8KT2gfSPqT9y9uBZAEY/Nhrl1zA30DkjhusmRvk3/9TUVLdTStUxYEdHR2OxWByjADDsHnYDuL1NVyOO06dPA8YIxWazlRnJ2Gw2t/YTQfAGJcXFPl12+vPPMHUqdO0Kb74JWmvW/nstAC07tWTY3cN8JkttECXRiEhPT3c8rBMSElzuuLZarSxYsIDZs2c7VhRlZWVV2GWdmpqK1Wp1GKYre2BnZmZitVqJiYlxLGG1j0xmz55NRkYG6enpFZa2pqSkOOwS9jqCg4OJiYlh1qxZbvdzCII3OJSezmfXXccPzz5LnvkC403mzYPiYsMVx9ChcGDlAY5mHgVg5EMjG7zB2o7suBYE4ZJg7ZNPsnfRIgJatOD21avxb+5dh3rh4ZCVBSEhsGcPzJ86j52LduLf3J8/HvgjrTq38mr7nuJux7XYJARBuCToOmYMeadPE9imjdcVxPbthoIAY4f16d2n2PnFTgCG3zu8wSmIyhAlIQjCJUG/W2+l3623+sQuYd9hDYaSWPvCWjCbHf3H0V5vvy4Rm4QgCJcU3nbJXVxc6qtp7Fjo1u4im9/dDED/yf3pNLiTV9uva0RJCILQpPG13XX5cjh82Pj/3nsh480MinKLABjzpzE+laUukOkmQRCaNJmzZpFvszHw7rvpOMz7y07fe8/4GxgIv7i1iHev/AGAriO60ndiX6+3X9eIkhAEoclScOYM2Z98QnFeHoXnzzPh9de93ubUqXDyJLRpA/rUafwCjAmb0Y+NbrDR5ypDlIQgCE2WwosX6TlxIgfS0hh4990+aXPaNOMoKQE/v848Yn2EHZ/uYPAvBvuk/bpGlIQgCE2WVt26Me6FF7jy+HFadPKtwdjPtPj6B/pzxR1X+LRtTzh+4ThrDq5xe14M14IgNHladu7s9amexrov+dX1rzJt/jS3532qJJRSkUqpbKWUNv+69VOtlIpXSiUppRLNI6my/IIgCPXJv/8NV18NyclwZNNxFv1mESd+PFHfYlXK+YLz/HfDfyvN4+uRRBIQAwQDWUCaUsriJu8MoD0QAoSZf93lFQRBcJCzYwffzZzJ4RUrfBam9L33YPVqePFF2PDKWja+vZE3hr3BuaPnfNJ+TXgr6y1y8nIqzeMzJaGUCgNitNZZWmub1jrGPOXOy5tVax1jHlHmcUkHR46KiiIqKoqYmBiioqJQShEeHk5MTAwxMTEuXXfHxcVVcO5nJz09nfDwcJRSxMTEEBcXR3h4OKGhoY4yycnJZfI412Wz2UhISCA4OJi4uDjx6io0GHZ+9BHH1qxhxcMPc/HYMa+3t3kzbN1q/H/33ZrCi4WgYNBtg2jTrY3X268JhcWFvLj2RQD6t68kroXWul4OjJFBdiXnk2pSb3h4uG6qxMbGOv7Pzs7WgE5LS3OkxcfHVygD6MjISLd1pqSkaEDn5OQ40qKjo7Vxa7jP40xl9QtCfZD1r3/p+REResUf/uCT9h57TGvDKqH1vn1G2sldJ/XJnSd90n5NeG/Te5pn0TyLTs5I1kCGdvFMrRfDtTnFlAhEVZKtvWmHyDGPSz5ijXM8BlfMmDGjzOfk5GQiIyMdEehc4SpO9siRI6udt7J0Qagvrvzzn5n63XeEOcVB8RZFRfDRR8b/EyZAnz7G/x36d6DDgA5eb78maK2ZvWY2AF1bd+We4fe4zetzJWE+7BMxRhJpSqmQSrInAf2ABCBeKRXvps5YpVSGUirjxImGbSiqDa5iWld2PiUlhZSUFIAyYUmrIi0tzRFQSBAaK4Ft2tCqe3evt5OeDvYZrXvcP2sbFF/t+Yptx7cB8MioRwgKCHKb1+dKQmudoLWO01qHAzYMReAqn7P9IhlIxTBmu8qbrLWO0FpHdPLxWuiGSlZWFmFhYY4IclVFoEtISHDYJMLCwiqEMRUEwTV2NxxBzTWBn85j4/82UpRfVL9CVcHs1cYook1gGx6MeLDSvPW9mS4diK5m3g14aXXTpnc2semdTTUuP+K+EYy4b4TL+u5bfl+ZvO9MeMdtubpk1qxZjpjScXFxJCcnk56e7jaUaUJCAiEhIWRlZTFz5kxiYmIcoxBBaCysf+YZOoWF0WfyZPwDA73e3tmz8Nlnxv93j9xJ9mLjKMwt5KqHr/J6+zVh/aH1fL//ewDiwuOwBFkqze8zJaGUitYVVydZMBRF+bxhWuuscskdAK88tWz7bOz/fn+Ny/ed0Lfa9Tmnly9XV9hjToeEGDN5YWFhhISEkJiY6FZJ2EOJhoWFkZKSQmhoKMnJyTLtJDQaTm7ZQvYnn5D9ySdcOHKEoQ895PU2N28Gf3/j/8E5azkHNG/XnOH3Dvd62zXFboto5teMR0c/WmV+X44kQpwVhWmLCMHYN4Fpb8jSWqcDkUop7IrCnldr7RUrlKWvhT7X9qlV+erW55xevlxdYbc/OBu6Q0JCHAbsqgzNduWSnZ1dJr06ZQWhvsg9cYKgjh3Jz8kh9PbbfdLm+PGGPWLBS4c58PQBAMJjw2nexruR72rKrlO7WLhjIQB3D7ubHm17VFnGl0oiHZijlIoD0gC01s6rm2Y45UsFksxt9FYgU5fuq6hz6nrap7L6yk8/eYP58+eTmZlZIV0pRXJyMvHxLu3/DuwroeyrnOxKIyMjo8JIxGq1OkYhglCf9Jo0ie7jx3NqyxZadunis3ZbtYK229cB4Bfgx6g/jPJZ257ywpoX0GaIvMfHPl6tMj5TEuaooOJur9Lz4U7/W6l8eazghtTUVLdTSnYDtrOScLU0dubMmYSFhREdbZiL7NNVcXFxpKSkOFZR2e0XYrsQGgr+gYF0jojwaZtnDpxhe8p2AIbMGELbnm192n51OXb+GO9ufheAWwfeyuBO1fNKKw7+GiHp6emOqaSEhARSUw1TT3JyMjNnziQrK6vCLuvU1FSsVis2m42YmBjH7mj7Kib7ru2oqChCQkJYunRpmfKZmZmEhYURExODUorQ0FASEhKYM2eOY6QhCJcKWsOrr8K+fbDulXXoYuPtfMxjDTfy3CvrXqGguACA+LGVzyY4o3RjdV3ohoiICJ2RkVHfYgiC4CMOffcd5w4cIPQXvyCwrW/e4jMyYORIaE4+fwl6EZ1XQN8JffnVsl/5pH1POZt/lt4v9eZM/hnG9hrL6l+vrpBHKZWpta4wDJORhCAIjRatNVtff52N//oXX8+Y4bN41va9EWFkofOMt/OGHL86OTOZM/lnAEgY59n6H1ESgiA0WvJzcijOywOg3y23+CQ8aGEhfPwx+FHCtUHrAegwsAP9J1fiJK8eKSgu4KV1LwEwuONgbh5ws0fl63sznSAIQo0Jat+eKYsWcWztWoIHDfJJm19/bcSwvoIfCcoz3s5H/3E0yq9hxq/+aOtHHDl3BDBWNPkpz8YGoiQEQWjUKD8/uo0b57P2jKkmzTi/tVACLTu2bLCb50p0icMFR/c23blr6F0e1yHTTYIgCNUkJwe++AJ6c4BuJcbbecRDETRr0ayeJXPN4l2L2XFyBwB/HP1Hmgd4vslPlIQgCI2Ootxctrz2GheOHvVpux9/DPn5MJa1APg392fkQ65d6zcEElcb/tvaNm9LbHjNXOyIkhAEodGxb/Fitr3xBotuuIETGzf6pM2iIkhMhCByCVF7ARh29zBad2ntk/Y9ZfWB1aw+aCx1/W3Eb2nbvGbLg8UmIQhCo+Pk5s0AtOjUiQ5Dh/qkzYAAWLQInnqqBf1ueJRBFzMZeOtAn7RdE+yO/AL9A3lk1CM1rkeUhCAIjY7Rzz3HgDvuIPfkSfwCfPcYGz4cvvwStG6BUlf7rF1P2XFiB4t2LgLg3mH30q1NtxrXJUpCEIRGSfshQ+qtbR9sx6gVL6x5AQCF4s9j/1yrukRJNDLCw8Np3769w2W33QNreno6VquVpKQkR+wIe5ChuLg4h7M+QRA849gxSEuDG0eeYt1La7ju+eto1alVfYvllsNnD/P+lvcBmDpoKgM71m5KTJREIyMiIqJCaFGr1UpycjKRkZGOIEHt27cnPDycxMTEKmNjC0Jj4cA339C2Xz8sAwb4rM3nn4f//lfzYOuv6Ho+mx2f7OD3u39Pi+AWPpPBE15Z/wqFJYUAxI+rviM/d8jqpkaGcyAhOzExMVgsFnHZLTRpCi9cYP1f/8qSadPY+MILPmnTaoWkJGhGIc2DjDmmwb8Y3GAVhC3PxpsZbwJwTZ9rGN1zdK3rlJFEI6P8qCAhIYGsrCzS0tIkapzQpDmekUHh+fMAdLzySp+0+cwzxtJXCOTur+6i9aGd9B7f2ydt14SkjCTOFZwDPHMHXhmiJBox6enpzJ49m/j4eLeBhgShqdDj2mu59auv2PvFF/SYMMHr7W3eDB99ZPw/fTpERCiI8I1/qJqQV5THy+tfBuCKzlcwuf/kOqlXlARgXbgQ6+efAxD5zjtlzq3685/JO3mSbuPGMWTmTEd6zo4dZCYauxnDExIIHlwa5Wn7nDkcXb2aoI4dubrcsDj9vvsACLntNkKmTauxzPbgQWFhYSSacghCU6d1r14Mfeghn7T1l79AC32RAr8gnn++4c/Mf7DlA46dPwYYjvzqyiOuKAng/JEjHN+wweW5U5s3c+HIEVp1714mveDcOUeZgnPnypw7u3cvxzdsqFAGcJTpPLJ2W/ljYmKw2WxihxAEL7BiBSxZormHT+gdfIHmxydD/4Y7zVSiS/jXmn8B0KttL+684s46q1uUBNC6e3e3D+0Ow4fTqkcP2vbrVyY9sE0bR5nANm3KnGvbrx+dR44kqGPHCvXZy7R2oUCqy+zZs0lPTyclJUVChwpNnvOHDnHh8GE6X3WVT+JFaA1PPglD+JFQrHAKtn64ld7jGq6S+Pynz9l1ahdgOPJr5l+HDge11k3qCA8P102ZzMxMDejY2FiX59PS0srky8zMdJtHEBoDP/ztb/rDyy/Xi6dO1YUXL3q9PatV686WPP0Y/9bP8qye3XG2vnja++3WlJKSEj1qzijNs2jLPy36bN7ZGtUDZGgXz9SGP9EmOLDbIUJCQirslQBjv0RWVlaV9cgUldBYKMrN5dCyZQC06NyZgBbeX3rarx+8fc8K2mJMI0fOjmywS14BVh5YyfrDRoS8h0c+TJvmbaoo4Rky3dSImDlzJlarlbCwMGJiYsqcs9lsZGRk8OSTTwIwa9YsRxnnKamsrCzZfS00GgJatGDK55+z9Y03CLn1Vp+0eXz7cTa+sQ6AnmN6MuJXI3zSbk2xBxVq7t+c31/1+zqvX5REI8KTEYCMFoSmQmDbtoQnJPikLa01X/3uK0qKSlB+iimvT2mwYUkBth3fxuLdiwG4f8T9dGndpc7bECUhCIIAvPkm7F20jZbL9wEw8uGRdB3RtX6FqgL7iiY/5cefxv7JK22ITUIQhAbHzg8+YOeHH1JibHf2OufOwXP/L5/ir74FoFWXVkz8+0SftF1TrDlWPtpq7Pa7ffDtXNb+Mq+049ORhFIqEkgCQgArEKe1Tq8kfwhg30q8QGtt87qQgiDUKxeOHmXTyy9TnJvLiY0bK2xI9QYvvghDTy2nDYbbj6h/RRFkCfJ6uzWlRJdw/+f3U1RiKNG6cOTnDl+PJJKAGCAYyALSlFIWVxmVUtFAHLAAOA1kussrCELTIffECVqYe4z6z5jh9fZOnIB3En9mFMYKoV5X92bY3cO83m5teHndy6zYvwKAB8MfJKJ7hNfaUsbyWO+jlAoD0FpnOaVpIFRrbXWRP0drHez0OQ3I0lpXasGKiIjQGRkZdSe4IAg+pzg/nyMrVtArKsrrbf3xUc2ZV96hDwfAT/Hgpji6DK17A3Bd8eOJHwlLCiO/OJ/Q4FA2PbiJ1oG1j7OtlMrUWlfQNj4bSWits8opiBDA6kZBRGJMRzmTRunUkyAITRj/5s19oiD274cVr20xFAQw6g+jGrSCKCwu5J6F95BfnI9C8e7Ud+tEQVRGvRiuzWmjRMDdXRCGMcXkjA2weE0oQRDqleKCAp+3+bcn87iuOA2A5h1aM/FvE3wugyf8Y+U/yDpqvGs/PvZxxvUe5/U2fa4klFKJGAoiBMMm4cr5UAcXaaeB9m7qjFVKZSilMk6cOFF3wgqC4BPybTYW3XgjW157jaLcXJ+0uW0bLPv4GAEYxt8p/7me5m2b+6TtmpBxJIPnVzwPGK7A/z7x7z5p1+dKQmudoLWO01qHY4wOKvqXcE/50YW9zmStdYTWOqJTp051IaYgCD5ky6uvkvvzz2x74w2OrV3rkzbz86F9WF9eVw9zxSPXccWdV/ik3ZqQW5jLPQvvoVgX08yvGe9Pe5/mAb5RaPW9mS4dcOUjIpuK9of2VLRTCILQBOg7ZQonN2+mucVCj4m+2Z8QHg4bNkBmZhtGjhzvkzZrylPfPcVPJ38C4NkJzzKi6wifte2zkYS5pLU8FgxFUR4rhl3CmVAM4/UlS3p6OlFRUSiliIqKIjU11XHOarWSkJBAcHAwwcHBzJ4922UdcXFxpKe73ZoiCPVCp7Awbpg/n3EvvOATd+BFecYUk58f1DK0i9dZvm85L617CYDRPUd7dU+ES1y5hvXGAcQD0U6fQzAe+han85FO53PK5c+0563suFRchbtyAa611iEhITo6OtpteUBHRkZ63K64FxeaCketF/WLPV/U3z3znS64WFDf4lTKmbwzus9LfTTPols830LvPLnTa23hxlW4L6eb0oE5Sqk4UzmgtXZe3TTDKR9AOJColLLr+ZladlxXicVioX17l/Z9kpOTiYyMJD09HZvNhsViqVadCQkJpKenk5mZWYeSCpc6Rbm5nDtwgOCBA33WZkkJJIz8jpBTZ1nx9xV0HdGVwdMGV12wnnjsm8fYf2Y/ALOjZjOgwwCfy+AzJaGNPRLhlZwPL/fZirE7W6gjUlJSSElJITg4mOTkZOLjqz9sdad4PMFms5Gens7p06eJiIggLKz8jKJwKfHjW2+xPTmZy6ZP58o//9knsSLmzYPvTg2nBYfoFtqSQVMHeb3NmvLFzi94e+PbAEzqN4mHRvomtnd5xMFfE8Nms7lMz8rKIiwsDIvFQmxsrCPeRFVkZWWRnp5ORkYGMTExzJ49m9mzZxMeHk5MTIzDvmEPiGQnOTmZ8PBw4uLiAEhNTSUhIYHIyEgiIiKIiYkhwUfun4WGR8G5c/z03nvokhJObd2KX2Cg99ssgKefhkP05PPOM3lo6e0+sX/UhJMXTzLzi5kAtG3elrm3zcVP1dPj2tUcVGM+LhWbRGRkpI6Ojq5w4Ca0aXR0tM7Ozi5TR3XsDDk5OTo2NlaHhYXpnJwcnZOTo7XWOjIyskw7iYmJGnCc11rrsLAwRx3lz3kig9A0se3erZf+5jf6+MaNPmnvv//V2ohgrfVrr/mkyRpRUlKioxdEa55F8yz63U3v+qRdGoBNokHy6NePsunYpnprf0TXEbx848sel0tMTHQ5XRMeXnFGz2azYbPZHBHqwsLCCAkJITExkcjIyj2dWCwWh53D2YZhHwnYw6hmZ2cTEhLimMbKyspihumcbcGCBY567NhlSElJqVIGoWnS7rLLuG7OHJ+0dXD7WT74yyFgMP36KWbO9EmzNeLjbR+T+qOxcnHqoKncM+yeepXnklcSm45t4vv939e3GF4lOTkZwDH1AxASElLBgB0XF+fIC5CUlERsbKzLOqdPn05cXBxZWVlYrVbi4uIIDw8nMTGR+Ph45s+fT2JiIuB+Cqy6hnNBqA1F+cW8dk0KN5w5RCihXP/UdAJ9ML1VEw6fPczDSx4GoFPLTiTdnFTvU2KXvJLw5aaU+mp//vz5LlcmKaXKGLCTkpIcI4OqsFgshIWFMX/+fGw2G0lJSYSEhDj2YXToUOpZJSQkxDGacVYMNpvN5chHaLrsW7yYFp060eWqq3zW5iuTv6Xl6UMAtO1t4e5fN0wFobXmgUUPYMuzAZB8SzKdW3WuX6EQJVGjqZ6GTPm39tTUVLfTOXYDdlWrnDp06IDVanXUb3/Qz5gxg4SEBEc8bbtRPCYmhqVLlzrKR0dHY7FYykxPWa1WR37h0iDv1Ck2PPcchefOMfj++7nyz3/2epubP9jK+e9+AOB4s+48vfpGGqitmqTMJL7J/gaAe4ffy9RBU+tXIBNZ3dSISE9Pd6wISkhIcLnj2mq1smDBAmbPnk1ycjIzZ850rFByJjU1FavV6liVZFcCroiONjbLBwcHl8lnf/jbz4MxZdW+ffsK9pLMzEysVisxMTEkJyeTmpoq+y4uMU5t2+YIR9rZByOJ49uOszjuCwCKmrXgprkxdO3ZMN+L95zew5++NWJU92rbi1dufKWeJSrFZ0GHfIUEHRKEhsuFo0fZ/9VXXP7rX3u1nfyz+cwZOYdTu06Bgru/vpvQ60O92mZNKS4p5tp3rmX1wdUApN+TzqSQST6Xo96DDgmCILTq1s3rCkJrTerdnxsKApjwtwkNVkEA/Hvtvx0K4ncjf1cvCqIyREkIgtCk+PbZNez5YgcAoTf155qnrqlnidyz9eetPL3saQAGdBhAYlRiPUtUkVopCaVUX6XUCPNv27oSShCEpkHhhQt8c9ddHPjmG3wxtW39bh9r/24smsjBQvM7p6H8GqaluqC4gHsW3kNBcQF+yo93p75Ly2Yt61usCtRISSilJiml9gApwGwgGfhOKfWNUqpvHconCEIjZtubb3Jq82ZWPfYYR1et8mpbZw+f5YPbUlFoivDnzA3Tib7b+/6gasrfv/87m3/eDMAT455gdM/R9SyRa2pq6o/WWl/m6oRS6s/ACzUXSRCEpkLbfv1obrHQpm9fuo3zXjzm4sJi3p2Sij5/AYB1HaaQOr9bg13uuu7QOmatMvynDe8ynL9O+Gs9S+SemiqJrDqVQhCEJknoL35Br0mTyD9zBuXnPRPokkfTOL35IABZ6kr+/sWVtGvnteZqxdFzR7nzkzsp0SUE+gfy/rT3CfRvmBv8oBab6ZRSs4ANGHGqwQgiFO70WRAEgcB27Qj04hN7+4LtZL2+HoAjdCPi6cmMGeO15mrFmbwz3Pjhjeyz7QPgH9f9g6FdhtavUFVQIyWhtZ6jlLoSI1CQhdL406la66WVlRUEoWlz6LvvsAwYQOuePX3S3uYT3TlKV9pxhv2jpvP6Mw1zw1xeUR63zbuNLT9vASA2LJY/jflTPUtVNTXqTaVUX631RmBjHcsjCEIjJmfnTlb/+c/4NW/O2MREelzj/eWn2aeDeZtf06/NKZamWPD393qTHlNcUswvP/2lw5notEHTeH3K6/XuvK86VKoklFL/BCYBSVrrt5xORSml7DGqrVrrfd4TURCExsLRVasozs+npLCQgKAgn7T59NMwenQz8vO70quXT5r0CK01Dy1+iE93fArANX2u4aPbP8LfrwFqMxdUNZKIBmLMUYMzp4EEjPCi/ZRSMVrrT70hoCAIjYfLH3iA1r16cfHoUa96el33yjoARv1hFEopoqK81lSt+dv3fyM5y3DBP6zLMD6/43OCAnyjQOuCKqebXCgIMGwQ4VrrM0opCzALECUhCAK9r7/eq/XvX7Gfb//0LbpYc/bgWa5/wbvt1YY3NrzB377/GwB9LX356pdfYQmy1K9QHlLVmjSbm/QMrfUZAK21rZJ8giA0cc4fPkxJYaHP2sstCuAcbSjCn9zQK3zWrqek/pjqCCDUsWVHvrn7G7q36V7PUnlOVSOJ064SXYwuQupGHEEQGhP5NhtL77uPll27Mu6FF2jZpYtX29Mank3uwRfFcfTgMB0LGuZDd9neZfzy01+i0bRq1ooldy1hQIcB9S1WjahqJJGilLquGvWIkhCES5DtyclcOHKEE1lZHCwXs8QbvPMOzJ8PF2lJ/8n9+cMfvN6kx2w8upHb5t1GQXEBAX4BfDrjU0b2GFnfYtWYSkcS5n6Ib5VSp7TWm13lUUr9BsjxinSCIDRohv3hDxSeP0/+mTMMuOsur7Wz49MdHD2m+H38IAC6dIG5c2lwbjesOVZu+vAmzhWcA+Ddqe9yfWjDtZlUh+rsk3gQ+FYplYbh0M+KMQ0VgrGZLh5jp7UgCJcYAUFBjPr73ykpLPTamv8TO07w2a8+o+B8AWFMZCXX8N570Ln+wz+X4efzP3P9+9fz84WfAXjphpe4a6j3FKevqM7qJitwmVIqEUgF7PvrFcYI4nqt9SavSSgIQoOipLgYv3I71vyaNfNKW2cOnOGjyR9RcL4AgGN05U9/Ai8voPKYc/nnmPzRZLJzsgHDq+ujox+tX6HqiGrvuNZaJwAJSql+GK44rPYVTp6ilLKYq6IqyxMPhFK6csoCpGitvT/xKQiCS0qKi1n+4IN0HDGCKx58sIKyqEvOHTnHe5Pew7bPBsAyJtAmbAD/939ea7JG5BflM23+NLKOGn5P7x9xP/83qYEJWQuq2nHdVmt91jlNa723po0ppZKAWPN/G5CgtU52k30GxtRWewwFgdNfQRDqge3JyRxbs4Zja9YQ0Lw5l//mN15p58LxC7wX+R6n9xgLLLM7jyLj/DVkfQyBDchhaoku4Vef/Yqlew2XdTcPuJnkW5IbhbuN6lLVSOIvSqnHgXQM9+AbgHRnxaGUuk5r/V1VDSmlwjDsGMFmUiKQpJRKN6e0ymPVWsdU5yIEQfANvaKi2L9kCQD977zTK23kns7l/aj3ObnjJAARv43g0Vk3cM8PigENaBWp1ppHvnqE+dvnAzCm5xjmR88nwK9hOhisKVVdzXwgG8NQPRKYAyillMZQHBsAq1Jqltb6ySrqCgHinKaZ4pRSsUAkRmS78rjcoyEIQv1huewybpg3j/ycHJq1alXn9eedyeP969/n5y2G8XfE/SOY/NpklF/Dc70xa9UsXtvwGgCDOw7my7u+bJDhR2tLpfskzE1zC7TWn2itnwBytNbtgShMozXG6qfIqhrSWqe6GTFkuCnSXimVpJTKMY+GFyFcEC5BmrVq5RU34Pnn8vnwpg85mnkUAL9hV3Bz8i0NMkb1W1lv8dR3TwHQs21Pvrn7G9q3aF/PUnmHKkNFlTNOZ5lpWVrrBzGmjBK11h7vFFFKRQNZWuvKotwlAf0wnAnGm8ZsV3XFKqUylFIZJ06c8FQUQRAq4ce33+Z4ZqZX2yi8WMjHt3zMobWHjDYZzLNbpvLlYu9Fs6spi3YuIu7LOADat2jPt3d/S692DdD9bB2htNbVz6zUJKCds8dXpdTtGCOMKu0STmUswFJgUlWrnJzKpAAhWutK92RERETojAx3gxNBEDzh0LJlrPjd71D+/ox+/nn63XprnbdRlFfEx7d+jDXNmGjYRX/mM4O77vHnnXfAi1FPPSYtO41b591KXlEeLQJasPTepYzp1UDD4HmIUipTax1RPt2j7jejzp1RSu1RSs1XSv0ZY/VRkofyzMFwQW7zoMwGxE4hCD6lwGbDr1kz/IOC6DB8eJ3XX1xQzILoBQ4FkU0IC5jOlFv9efvthqUg3tv8HpM/mkxeUR7+yp+UmJQmoyAqw2MzvNZ6qVIqHJiOsdM6BPikuuXNEUGCG/uEPU+Yi2moDhg7vgVB8BEh06ZhGTiQ3OPHadunT53X//mvP2f34t0A7KMP87iD8RMDmD8fvLQ/z2O01vxj5T94etnTAAT6B/LBtA+YMmBKPUvmG2oa4/oMxmhgjiflTAUxH7CYS2Lbm/Wlm/aGLHOzXKRSCruiMKPghZgb+gRB8CHtL78cLr/cK3UPv28EW+b/xKGiLnzEnQyPaMbnn4OPgtpVSVFJEb/98re8tdEIzGkJsvD5HZ9zTR/vh2VtKFS1me7PQGpdhCc1N9JFm0eF0xib58BYWpuKsYcCjA11mbJnQhB8w+758+kxYYLX3X4DbLSF8FbRrzhFB0IHN+err6BNG683Wy3OF5xnesp0vtrzFQC92/Xmq19+xeWdvKMwGyqVGq5NQ3UCoDFWMVXbOF1fiOFaEGrOjnfeYeO//kXrXr247u23ad2jR53Wr7URTa5db8MFXEkJ/P73sHgxrFoFXlhZWyOOnT/GlI+mOFxtXNn1ShbftZhubbrVs2Teo0aGa631Uq21fS/Eg0qpDaZrcEEQmhhaa84fMpagFl28SElBQZ3X/81j3/DmiDc5vOEwYBimX3sNNmxoOArip5M/MebtMQ4FceNlN/L9fd83aQVRGdVaO6C13qu1no6xae4ypdRupdQspVRb74onCIKvUEoR8dRTXPHQQ0ycM4e2/frVaf0H1xxk/cvrycvJ48sHF2OfxVAKOnWq06ZqzMr9Kxn79lj22fYB8MCVD7DojkW0ad5A5sDqAU+XwJ7RWj+hte6PYSv4zlwKO8Ir0gmC4FOUUgx7+GGCBw6s87p7j+tN6CNTyMHCFy1ncOFCw9pJnbI9haj3o8jJM2Ko/W3C35hzyxya+TeQZVb1RI1XIWut55jzV8nAbKXUN9UMdSoIQgPhyMqVZP7zn+iSEq+3tX49PPhWBK/zEN+ub8fGjV5vstq8tPYlpqdOJ784nwC/AObeNpdnrn2mSXlzrSm1dldobrBbasaZiAQavHFbEAQ4npnJykceoTg/n+K8PK569tk6b2PLB1sIiQxh38nW3HQTXLgASjVj/ocwfnydN+cxxSXF/OnbP/HK+lcAaBPYhtTpqY0+5GhdUmc+bc04Ex7tmxAEof5o3bMnrXr04Nz+/XS7+uo6rVtrzcr/W8my/7eMtv068PqFe8nJMUyYSUkQ0wAWtOcW5nL3wrv5dIfhZahb624s+eUSRnQdUb+CNTBqpSSUUn0xAgHZgNPlAxQJgtBwadmlC5HvvMPJLVvoOXFindVbXFDMF7FfsPndzQCc2H+BcyUXgbYkJsLMmXXWVI05efEkt827jTUH1wAwpNMQlvxyCb3b9a5nyRoeNVIS5v6JJAx34Tlmcnul1CmMmBH76kY8QRDqkpKiIvwCSn/2QR061KmCyD2dy/xfzGf/9/sBuNDMwjuFd3GCTjzxBMS79OPsW6w5Vm784EZ2nzbcgUzoO4GFMxZiCbLUr2ANlJoarqO11pdprUdqra83jwit9Q243lEtCEI9c/7QIRbfdhtH16zxSv2ndp/irdFvORRE28t7klzyACfoRGwsDSI29YbDGxjz9hiHgrhr6F18/cuvRUFUQk2VRGUxIARBaGAUFxSwLDaWc/v28f1DD3F2b41D1btk/8r9vD36bU7vNhw1D5k+hN9l3MvLb7Xmvvvg9deN/RD1yRc7v2DCuxM4fuE4AE+Me4L3p71P84Dm9StYA6fGNgml1CwM9902MykEwyuszU0RQRDqCf/AQIY/8ghr4uMZeM89tOnbt87q3vz+ZhY9sIiSQmMZ7finxjPx7xNRfor77oNf/ap+FURhcSHPLHuGxNWJaDR+yo/XbnqN3478bf0J1YioysHfm8AGrfXbzula6zlKqSsxnPJZMLy5WjGcAS71kqyCINSC3jfcQNt+/WjXv3+drP/XWrP8r8tZ8dwKI8Hfj7SgW7jrVyNQTnMU9akgrDlW7vzkTn44/AMALZu15OPbP+bWgXUfPKmpUtVI4gkgXSmVrrXe73zCjH/dgLbDCILgTOGFC+iSEgKd3KpaBgyok7qL8or4/Nefs+3jbQAUBwbxfsEM9l3oy113wQ8/1P/00sdbPybuyzjOFZwDYHiX4cyLnsegjoPqV7BGRlUO/mwYG+TmyG5qQWg8FOXl8f3DD/PdAw+Qb7PVad0XTlzgvUnvORREbov2vF7wG/bRl7594b336ldBnC84z68//zV3fXqXQ0E8MuoR1v1mnSiIGlCl4VprbTM9wYYrpd5w5dRPHP0JQsNi5/vvc3zDBk5v3862N96os3ovnrrIW6Pe4uCagwCcaNmbV3Mf4BQduOoqWLcOBg+us+Y8JutoFuHJ4czdNBeAji078sWdX/DyjS8TFNBAIhk1MqptuNZa/0sp1Q54UillAdKAbK31ZuBJ8xAEoQEw+L77sO3eTd6JEwz/4x/rrN4W7VsQen0omUmZ7AwaxoKLt1BMANOmwQcfQMuWddaUR2iteXndyySkJ1BYUgjAdf2u4/1p79O9Tff6EaqJUGnQIUcmY2d1NBBlHlaMVUxhZhattfb3joieIUGHBMGgpLiYkoICAlq0qNN6074p5i+3biOjYBigeOwxmD0b/OvpCXD8wnHu//x+luxeAoC/8uf5657n8bGP4+/XIB5LjYIaBR1SSrVVSn0DZAN3YIQWDTU30kVorf2AywBZ0SQI9UjuiRNsnzMH55c+P3//WisIXaJZ98o6Cs6XBiC6Ypg/x7sOx89P8dpr8O9/15+CSLemM/zN4Q4F0dfSl1W/XsUTVz8hCqKOqGq6KQsIBq53t7RVa21VSiXWuWSCIFSLM9nZLIuL4+LRowAMqSPnSIW5hSy8eyE7Pt3B3qV7mbFwBn7+fnTrZoQb3b8fpkypk6Y8l624kKeXPc3s1bPRGIpxxpAZJN2cRLugdvUjVBOlKiWxEcPuUOlIQfZGCEL9Edi2dN3I+UOH0FrXyT4I/2b+FF405vf3Z53m4smLtO7SGoArrjCO+sDV3ofXbnqN+0bcJ/EfvEClSkJrHWMaqwVBaKC06NSJCW+8wdFVqxh0X909KP0C/Lj6lWjSr05n3uFJ9FsexIwZdVJ1jSm/92FE1xHMu30eAzvWfSQ9waBKm4TW+oyvhBEEoWp0SQm2XbvKpFn692fw/ffXSkEUFxaz9qW1FOUVAbBtG1wT1Zx3TkwhjyA+/BCqsc7FK5wvOM/9n99fce/DA+tEQXiZqqab/qKUehzDYJ2F4asp3TluhFLqOq21RKMTBB9QlJfHur/8hcPff8+kuXPpOGxYndR7es9pPrnrE45sOMKZ/Wfwn3Ij0dFw1vyl/+Y39eek74fDP3D3p3c7PLd2bNmRubfN5eYBN/temEuQqjbTzQcexIhjrTAiz+1TSp1SSs1XSv0ZsJjO/gRB8DKnt23jYFoaxXl5bHrxRaqzhL0ytNZsencTSVcmcWTDEQDWztvPlOsLHQpi1ixIToZmzWorvWfY8mw8vPhhRr812qEgJvWbxOYHN4uC8CFV7pNQSrWzTzkppfZorS9TSoUBsRieXwGCtdYjvStq9ZB9EkJTZ/e8eez/+muueeUVAtvV3GSYZ8tj8W8Xs23eNkeatctoPvx5EsUEEBQEc+fCHXfUhdTVR2vNx9s+5rFvHuPnCz8DEOgfyN8m/I34cfH4qZpGOBAqw90+iWptpnOqZIHWerrT50nQsFY3iZIQmholxcX4lduI4CrNEw6uOcgnd33Cmf2GybFVl1YU3TKVJ9+6DIDhw+Gjj+Dyy2sud03YdWoXDy1+iKV7Sx8p1/W7jtcnvy62By/jTkl4Gk8iSSn1C631p2AoB6XU7Z7aJZRSFtN5YFX5QjAcDAIsqE4ZQWhKWD/7jF0ffcSk//2PZq1bO9JrqiBKikpY+X8r+f5v36NLjBfE/pP7c9vc22jRsRVL98HQocYUU3MfxuLJK8rjn6v+yaxVsygoNjbudW7VmRevf5G7ht4lS1vrEY+UhKkUJiml9gCZGIbsM8A/gf5VlVdKJWFMU6GUsgEJWutkN3mjgZHALAxFkamUChdFIVwqHFm5knVPPQXAmiee4NrXXqtVfbb9NhbevZADqw4AoJr5M/IvUdz416scD+ElS3xve/g2+1seXvIwe07vMeRC8WDEg/zjun8Q3CLYt8IIFfB4cs+cWgrHWPF0GRADfFJVOdOOEYKxgzsYWIAxMglxU2SO1jrB9EKbiuEvSpwICpcMXceOpceECQS2a8fg+++vVV3bF2znzeFvOhSE7tiRN4t+w/8tHUVJSelbui8VxNFzR7nzkzu54YMbHApiRNcRrH1gLa9PeV0URAPBI5tErRoyRgZZWmurU5oG4sqPJpRSkUCi1jrcKS0emOGc5gqxSQhNicILF8g7dYo2vXvXqHzB+QK+euQrNv1vkyPtQJdw3v/5BgppRvPmsGIFXHVVHQlcDYpLinkj4w2e+u4pzuYbS6haB7bmuYnP8burfkeAX42jKgu1oK5sEjXGHA24wtUTPQw4XS7NhhEqVRCaJGf37ePAN98wJDbWMf3TrFUrmrVqVaP6Lpy4wP/G/Y/Tu42fkl/rFiwsupWNPxuBd664wjBODx1aN/JXh8wjmcR9GUfm0UxHWvTl0bx0w0v0bNvTd4II1abeVLbTyCLLxekOLtJOY8TSdlVXLKato3cN37gEoT45sXEj3z/0EAVnzxLQsiWD7rmn1nW27NiSLkO7cHr3aS526csbP0/jHIafp9/9znDvXcdexN1yJu8M/++7/8frGa9ToksA6Gfpx2uTX2Ny/8m+EUKoEfWiJMygRU8CkzwsWn50AYA5XZUMxnRTrYQThHqgbb9++AcFwdmzFJw9W3UBN+gSjfIzRiFKKfo9cgvvLu/NVz9fhcaPTp2MvQ++8t6qtWbB9gU8+s2jHDt/DIBmfs14fOzjPHXNU7RsVk9RioRqU18jiTlATCUrlbIpXfpqpz2G8VoQmhzNLRbGJiaSn5ND7xtu8Lh8SVEJ619dz5b3t/Dr1b+mWQvDAt09tAXrGI0GbrgB3nkHunatW9ndseXnLTye9jjfZn/rSLu2z7W8MeUNBneqxxingkf4XEkopVIwlr5W9sC3Uhr1zk4oRshUQWjUaK3Z+cEHNGvdmtBp0xzpXWphPd7y4Ra+fcx4GK/65yom/m0iAD16wP/+B3v3wh/+AH4+2Ky8N2cvzyx/hg+3fOiI9dCxZUf+ff2/uWfYPbLnoZHhUyVhKoj5GP6ewjBtDFrrdHP1UpbWOt38bFNKRTsZvCPxfHpKEBoc6595Buunn+LfogUdhw+nXYi7VeDVZ9gvh7H+lfWcPFLAhp/7MNHp3G231br6anH8wnGeX/E8b2a86Ygz7af8mBk2k/+b9H+0b+HSpCg0cHymJMyNdNHmUeE0YPdUn27+DQcSlVJ2n1AzZSOd0BToO2UK1oULCQoOpujiRY/La63ZNm8bPa7qQftQ48G7dbsfC9QMVvzcGv1WAON/BWPG1LXkrjmbf5Z/r/k3/177by4UXnCkR18ezXMTn2NQx0G+EUTwCr5cAhsHxFVyPrzcZyvGRj1BaNSUjxTXdfRoxv3rX3S7+moC27TxqK5Tu0+x5OElWNOshF4fyi0Lfslf/6p49VUoKbEA0KMrnDtXl1fgmvyifN7IeIN/rPwHJy+edKRP6jeJWZNmMbJHg/D5KdQS2bUiCF7kTHY2P/z1r4x67jna9uvnSO9z000e1VOUX8TqxNWs/L+VFOcXA7Bv3TEiBpxlz3HDE6y/P/zxj/DMM+Ch7vGI4pJiPtjyAc8sf4YDZw440sO7hfPPyH8SGVJ+zYnQmBElIQheIvfkSb6ZMYOi3FxWP/4413/0Ef6BgR7XY11qZclDSzi165SRoOBI93DeOzyJvLPGRofx442gQN6MO6215otdX/CXpX9h+4ntjvT+7fvzj+v+we2X3y5uvJsgoiQEwUu06NiR/nfeyY65c+l29dUer+o5//N5vv3Tt2z9cKsjrcvwLvT67c3c/KCxO7lTJ3jhBbjnHu9GjVu5fyVPLH2CNQfXONK6t+nOX6/9K/ePuJ9m/j72Cij4DFESglCHFBcUlBktDPv97+k5aRKdRoyodh26RJM5J5OlTywlz5YHQLNWzZj494mM+sMo/AL8eGCD4cr7+ech2It+8Lb8vIUnlz7Jkt1LHGmWIAtPXv0kv7vqd7IZ7hJAlIQg1AElhYVsff11jq5eTdQHHzgUhX9goEcK4tjmYyx+cDGH1h1ypOV0GcS4529kzG9Ko9DNmePdkUP26Wz+uvyvfLT1I8dehxYBLXhk1CPEj4sXD62XEKIkBKEO2D1/PtuTDWfGW159lSv/9CePyufm5LLi+RWsf2U9utj0LNOuHakXb2LbzwP57HmYfCfYff15S0FsPraZxNWJzN8+3+FjyV/585uw3/DMtc/QvU137zQsNFhESQhCHXDZ9OnsXbSIksJCQjzcvbbzi518du9njqkl5e/H9rajWZhzLYUYI5IJE6CgoFRJ1CVaa1bsX8E/V/+Tr/d8XebcjCEzeG7ic/TvUGVMMaGJIkpCEGrAz+vX037IEEdIUf/AQK557TWat2uHv4dxPzsO6kj+uXwALnbqzTsnJnM8pwtgrFZ6/XVj9VJdU6JL+GLnF/xz9T9Zd2idI91f+XPHFXcQPy6eYV2G1X3DQqNClIQgeEDRxYusf/ZZ9i9ezMB77yU8IcFxrmXnzlWW11qz5+s9hESG4N/MiFPdoX8HAm64jvlLO7HlxABA0bo1PPus4W+prqPFFRQX8PHWj0lcnciOkzsc6UEBQTxw5QP8acyf6Bfcr5IahEsJURKC4AH+QUFcPHoUAOvChQx98EEC27WropTB2UNn+eTOTziw6gCTX5/MyN+W7kgOnHg1W8wFRNOnw4svGs756pLzBed5K+stXlz7IgfPHnSkW4IsPDzyYf4w6g90blW1ohMuLURJCEIVOLvVUH5+jHzmGba+/jph8fHVVhAALTu15OxhI1bE94k/EBEX4Yj98PDDsHIlPPIIXHdd3cp/6uIpXv3hVV794VVO55aGZOnWuhuPjXmM2PBY2jZvW7eNCk0Gn8W49hUS41qoKwrOnmXzf/5DcX4+o597zuPydoXQtofxAC4uhjmPbmfp+0dIy72arXta0KtXnYpchgNnDvDi2heZkzWHi4WljgT7t+9P/Lh47hl2D80DPLOfCE2Xeo9xLQiNjcxZs9i7aBEAIbfdRueICr8fl+TZ8liVuIr1L69n8C8GM+2DX7BoEfy//wfbtg0BhgDw6qtGCNG65scTPzJ79Ww+3PohRSVFjvTwbuE8efWTTB00FX8//7pvWGiSiJIQBDcM/d3vOPDtt3QYOpSgDq7CrpelKK+IH/77Ayv/sZK8HGM569aPt/LajxNYtqk0lkLXrvD00/Cb39SdrMUlxSzevZjXN7zON9nflDk3qd8knrj6CSb1myQBfwSPESUhCEBRXh4H09Lod8stjrTWPXpw4/z5tA0NrfThWlJcwpYPtrDs6WWcPVgan/psu56knonkgKkgLBZISIDf/77u9jucuHCCtze+zZsZb7L/zH5HukJx++W3kzAugYju1RsBCYIrREkIlzynd+xg1R//yPmDB2nWqhU9nSzH7S67zG254sJitn64lVX/XMWpnacc6R0HdaTDjEnc+beBgKJlS3j0UXj8cUNR1BatNesPr+e/G/7Lgu0LKCgucJxrE9iGe4ffy++v+j0DOw6sfWPCJY8oCeGSp2XnzhScOQOA9bPPyigJVxTmFrLx7Y2s+dcazhw440hv070NE/42gRH3jUD5+/HueujfH556Crp0qb2cuYW5fLztY/674b9kHc0qc25IpyE8PPJh7h52N22aezGYhHDJIUpCuOTIPXmS5u3a4WfuUgvq0IGwhAQKL1yg/x13uC2XfzafDW9sYN2L67hwvDRMZ3HLNnyXN4ankyIIu7l059vixeBXB+EVsk9n80bGG/xv4//IyctxpAf4BTBt0DQeHvkw1/S5RuwNglcQJSFcMhTl5rI9OZmf3n+fsPh4+k+f7jgXMnWq23K6RLPsr8v44dUfyD+T70jPbxXMtxfGsenicIoJ4Om/w/VTSp3v1UZBFJcU89Wer/jvhv9W8KfUrXU34sLjmBk+UxzuCV5HlIRwyaD8/dn35ZcU5+ay7fXXCbnttmr5WVJ+isPrDzsUxPlWnfnmwtVsvzCEEgxNcPPNRtjQ2r7Mn7x4kv9t/B9vZrzJXtveMueu7XMtD498mKmDpkqQH8FniJIQmiwlRUXo4mKHIvAPDGTo737H7o8/Zvijj7pVEKf3nCbPlkf3iNK39K7Tx5OxKp9vcsez68IANIpmzeDeXxoG6csvr4WcuoQV+1cwd9Nc5m+bT35x6WildWBr7h12Lw+NfIghnYfUvBFBqCGy41pocmitOfjtt2z+z3/oO2UKQx96qPRcSQko5Xb+fvHDi8l8M5OuV3Zl5oaZjnzHjmn69oH8AkWbNhAXZ7jQ6Nmz5nLuzdnLu5vf5d3N77LPtq/Mucs7Xc5DEQ9xz/B7xGWG4BNkx7Vw6aA12996i3P79rFj7lz633EHQe2NvQqqCkNBq86t0CWao5lH2b3iGAOu7QZA166Kx+ON/Q0PPljzpawXCi6Q+mMq72x+h+X7lpc518yvGVMHTeWhkQ9xbZ9rxRAtNAhESQhNgpLiYvz8DVcTys+PEY8+ypqEBIbMnEkzFzvXSopL2L14N+ePnSc8NhyA3bth/t5RHPc7w6qSMQSt60zCtaVlauC+CTBGNisPrOSdTe+Q8mMK5wvOlzkf3i2c+0bcx51X3EmHllXv7BYEXyJKQmjUnMnOZst//kNQhw6MfOYZR3rXsWO57dtvCWjZskz+3JxcNr69kQ2vb8C210azls3I6zeYl5Ja8umnoHULwIgst3597WTbb9vPe5vf453N72DNsZY517lVZ+4eejf3jbiPoV2G1q4hQfAiPlcSSqkQIAHI1lq7dW+mlIoHQgGbmWQBUrTW6d6WUWg8bPz3vzny/fcof38G/upXtO3TBwClVBkF8fPWn/nh1R/Y8sEWinJLnd7l5vvxq+uPkE3pzuqbb4b4eLj6as/luVh4kU93fMrcTXP5bu93Zc4182vGLQNv4b7h93HjZTfKCiWhUeBTJaGUSgMizY8JleUFZgBWoD2GgsDpr3CJUlJY6NgEBzDs97/n6KpV9L35ZgKCgsrmLSph56Kd/PDqD+xbvq/MuaBeHfnk4FVsLh5OAYEEBMAvzZVKQzxcRKS1Zs3BNczdNJcF2xdwruBcmfNXdr2S+0bcx11D76Jjy46eVS4I9YyvRxJZQAywtBp5rVrrGC/LIzQSTm7ezPY5cygpKmLim2860tsPHsxt335Ly65dHWkXT14k660sNry+oYzDPRQMvGUgV/3+KnpP6MfroYoWZ+B3D8Af/+jZSiWtNZt/3sy8bfOYv31+hdVJHVt2dEwnDe86vKaXLQj1jk+VhNY6Aajuqo3TVWcRLhX2fvEFh5ctAyBnxw6CBw92nLMriKMbj/LDqz+w7eNtFOWVTinl+wWRUXIlT382kvG3BjvSv/gCLrsMypktKmXHiR0OxbDz1M4y5wL8ApjSfwr3j7ifm/rfRKB/YE0uVRAaFA3ZcN1eKZUE2H0nJNuVjNC0KSksJPfECVp1L93MNvi++7B+9hl9p0ypEDI0NyeXebfO48CqA2XSj6vOrNdXsaVkKIUE0vdLGH9r6flhw6onT/bpbOZvn8/87fPZ8vOWCufH9hrLjCEzuOOKOyRGtNDkaMhKAiAJw3YxHUhSSp2qzNgtNH6yFy5k63//S/N27bgxNdUx6mzdsye/WL6cZq1bVygTZAki12bsUtYodjCIH7iKfboPoBgwAH77W/jVr6ovx8EzB1mwfQHzts8j40jFzZnh3cK544o7mD5kOr3b9a7RtQpCY6DBKoly9ohkpVQUhjG7gpJQSsUCsQC9e8sPtjFz8dgxLh49ysWjRzm2di3dxo51nPMPasmuxbvY+PZGwmaG0f+m/oAxfbm/99VkbjtGBiM5Qzv8/eH2qYZyuO666vlUOnb+GKk/pjJv2zxWH1xd4fwVna/gjiF3MOOKGVzW3n2cCUFoSjRYJeGCDbhZ3aS1TgaSwXDL4UOZhFpw4cgRzh8+TJeRIx1pA+68k0NLl9J/xgw6h4eXyV+UV0TqjFQKLxRiy8GhJADunX0Fs5dcQY8e8FisERq0ezUcpJ66eIpPd3zKvO3zWL5vOSW6pMz5/u37c8cVdzBjyAzxnSRckjRIJaGUCtNaZ5VL7gCk1Ic8Qt2z+ZVX+PHtt2nRuTO3fvWVY1lrc4uFm1JTKbhQwNZ5PxIyKYS2PduiNfywKRBbjyE027Wd9HUtuS9f07y5MUQYMgSWLTP2NgRUcVcfOnuIz376jIU/LeT7fd9TrIvLnO/drrdjxHBl1yvFPYZwSVOfSqKM/wFz81yWuVkuUimFXVGYG/BCxHDddGjVrRu6uNiYVlq/nu5XX43WmsM/HGbj2xvZNm8bBecKGP7oBDZbruW998BqhdZMooAbKchrzt1fw223ldY5YYLrtrTW7Di5w6EYXNkYurXuxvQh05kxZAaje44WxSAIJr7eTBcJRAFhQIj5Q5yltbZh2BsA0oFUDEM1GBvqMmXPROPk4vHjZKemovz9uSIuzpHe77bbOLV9O/1nzKB5pz6sfXEtG/+3kRPbT5Qp/+XLe3ibUgdKeQGtmTwZ7r0XbrzRfbsluoQfDv/Awh0L+WznZ+w6tatCnp5tezJ14FRuv/x2xvcej7+ff+0vWBCaGOIqXPAqy2JjObp6Nc3atGHad985XGWUFJWQ/W02G9/eyM5FOykpKrUFKH/FkZb9WX7uSnbTnxL8ufJKY3XSnXdCZzerTAuKC1i2dxmf/fQZn+/8nKPnj1bIc3mny5k2aBpTB00lvFu4jBgEwURchQtep+DsWYpyc2nZpYsj7bLp0zm6ejWte/Xi4s8/U5Dfhs3vb2bzO5s5d6Ss+4r2/dtz5QNXMvze4cz5uA2f/wseu9sYNQx14wPvXP45vt7zNQt/Wsji3Ys5m3+2Qp4xPccwddBUpg6ayoAOA+r0mgWhqSMjCaHWaK3JeO45rIsW0SsqirGzZjnOlRQVcej7DA5mFbPt420c23isTNkCmrGdIVgmjGDud70db/a5udCsmWsj9KGzh1iyewmLdi4i3ZpeJpIbGI70rut3HdMGTePWgbfSrU23ur9oQWhiyEhC8BpKKfLPnKE4N5cDX31FWHw8QcGG+wu/gABWvWhl95LdZcocpCcbuZLtDCGf5kzyB61L9zO0aFGat6ikiHWH1rFk9xIW717sctdz68DWTO4/makDpzK5/2TaBbWrkEcQBM8RJSF4xLkDB9izYAHdxo2j65gxjvQBd95JUW4+gd1Hc3DtCfpPLvWRVDDwCliym5N0YCtXsI2hnKID/frBE/fCPfdAaGjZdk5cOME32d+wePdivtnzDTl5ORVk6dyqM7cOuJVpg6dxXb/rCAoIqpBHEITaIUpCqDbF+fl8HRND4fnznLFayyiJTuHhbLt7Had2ZtNuWBGPTi6d+5/420GMfWkmR+hGx46K239huOW++mqwRxMt0SVsPLqRJbuXsGTPEtYfWo+m4lRoRPcIpvSfwuT+k4noHoGfqjwcqSAItUOUhOASrTUnsrIIHjTIEf7Tv3lz+k6Zwu7587lwNIcTO36m0+AunDsHX36p2FE8gM6s5eiW45w4lE+nns0B6NM/kD/8szthYTBxYqmd4UzeGdKt6SzevZiv9nzFsfPHKsjRtnlbbgi9gcn9J3PTZTfRpXWXCnkEQfAeoiSECpw7cIBlsbGcP3iQUc8/T+i0aWitObbpGKeOD+Dk+dvZ/Zk/2XlZfN/yJpYsgbw8aE84nejDHkIZujyAu+8urTMhwVA8245v45vsb1iyewkrD6ykqKSoQvtDOg1hcv/JTOk/hbG9xkoEN0GoR0RJCBQXFOAfWBr7oFX37hTl5gLw0wepZK9pxU+f/kSO1W4XMDad7f96Bwu5EY1hbS6xdGDstA68PN1wqgdw9NxR0q3ppFnTSLOmuRwttAhowXX9rmNK/ync1P8m+lr6eu1aBUHwDFESlzA5O3fy41tvcWTFCm75+muCgoMpKSph/8qDqOCrOXvgKNbPu1BcvLZMubOW3qywXcGPXE7bdoqpU2H6dIiMhCJ1kRX7V/DkMkMpbD2+1WXb/Sz9mNJ/ClMGTOHaPtfSolkLl/kEQahfRElcwhSeO8f+JUsAyHjhXU7/HMLOz3dy8eRFIBDoY2RU0Htcbwb9YhCX3345i1e14/hX8Mx0iIwqYUfOJtKy0/j3vG9ZdWAVBcUFFdpqE9iGif0mEhUSRVRIFAM6DJDdzoLQCBAlcQmQd+oU+7/+mnMHDhDx5JOO9E5hYfi17My5ky1Z/VI2eblnHOdKUOylHzsYTLdrB/LXZW0c58ZPOUje4DQ+sqbx61fTOXnxZIU2/ZU/V/W4iqiQKK4PvZ6relwltgVBaISIkrgE2DF3LjvmzgWlCJl2J+0H9QVA+flxIOD35O4zpoSK8CebUHYwmJ0MpGf/Ftx2G0y6+TQLdyxk2b5lpFnT+OnkTy7buaz9ZY6RwsR+E7EEWXx0hYIgeAtREk2IvNOnOZSeTvPgYHpFRTnSe1wXyY65cyksaEnac+nM+PA3jnPB1w4jY10xPzKYPfTnytHNue3WM3S+Kp3dhctI37+Mfy/f7HLPQnBQMJNCJjkUQ7/gfj65TkEQfIcoiSZE+q9+xVmrlTahg+ky5lqatQpk61b46tvhXDgag38OnDtc5PDJDhDzxGUs/KkLkyJXcW3P9/jhxDKeO5pFyaqSCvU382vGmF5juD7keqJCowjvFi7utQWhiSNKohGSl5PDofR0uo0bR6vu3Sk4X4A13UpuXi/ASs5P+/jzLdv4ZFcYR44AKEZzAx05yY6Ll/PQwQtkF6xh2b5lLNu3jA1hG/jqVDGcKttOgF8AI7uPZGLfiUzsN5GxvcbSslnLerhiQRDqC1ESjYzzhw/zxU03oYuL6TAmhpOH+7N32V6K84sJaNaKgGYTybvYkQO7D3KEMKNQQB4HR+XDNRm06vwvBr2zjsKSwgp1+yk/wruFO5TC1b2vpnVgax9foSAIDQlREg2Y3JMnOZGZSe8bbqCkuITD6w+z84udFBW3wR8bB9JWcuSA0zJSfwvb865ka/Pu7A05Seg1T6J7reRgyQYOlxRwGKB0ARMKxYiuIxxKYXzv8eI9VRCEMoiSaKBYP/uMdf/v/4HWNB/yR3al5VBguwhAy9ZXoEsCyL3YkRad29D1Fx3JGZPD7uDdLN+SyuGiLZRQYuiDcl4vhnYe6lAK1/S5hvYt2vv82gRBaDyIkqhnSgoLOZGVRVFuLj0mTHCk+7XtYwRYAA59t5QC2yAANJrMZn3Y1Ocsh/vtou1VmRzJ3w17MQ4nFIrhXYdzTe9rGN9nPNf2uZZOrTr56MoEQWgKiJKoZ9IfiOVk5g/QvDO3rx5P8xbGaqFe1w7nyIkICs+3xtpGkTVyP9Y+h7kQspXClqWxm887BWUL9A9kZPeRXNPnGsb3Hs/YXmNl+kgQhFohSsJHnD98mMPLl9Plqquw9O9PXh6sXQs/7u1HZ35A553gm/9s4ro/DmTD4Q2sObiG5Bl7OdxqC8Utzriss3Vga8b1Gsf43uMZ32c8V/W4SgLvCIJQp4iS8DJaaw6v3cWKmb8AIKd4DJ/3fouVKyEvT9Oj49VMCFnKTx3zOJJzD8f/uYtiXWwU7li2rk4tOzG+z3hDKfQez/Cuwwnwk69QEATvIU+YOiTfZuPoqlUcWb2eNsNjsKbtxfqtlbOHztKrX3v8W53kUItNLDufSNGtG6DXGg63OcqHzpU4bWy+rP1ljOk5xjFSGNhhoDjFEwTBp4iSqAPyz+az7/v9ZL35IXpfKgAHXj7LKf9ADvY6yMGogxzus5dDXY9THFAMZFaoIyggiJHdRzK211jG9hrL6J6j6dyqs4+vRBAEoSyiJGrAnpRP2f3pEmynWrB3zwgK9h2m2K+QEz33cnHEKfYE57Pr+rmcspxzW0f3Nt0Z12ucQymM6DqCQP9At/kFQRDqA1ESVVCUm4tfQAB+zUrdXC97di7nWv/EzrbFbBr0A4cnHeZot6OU+Ff0dwSG2+wRXUc4FMLYXmPp1baXTB0JgtDgESXhhpzd+/j6gccpPrWTs+GxhDxzGesPrWf94fWsmPo9FwIvmjn3VijbuVVnRvUYxeieoxnbaywju4+kVWAr316AIAhCHeBzJaGUCgESgGyt9exq5I00Py7QWtu8IdO5Awexpm3kfP8prFhXzNcbt7Dp6PcMC01jz1W5HGvze8pYl51mhZr7BRHePYxRPUcxqscoRvUcRZ92fWSUIAhCk8CnSkIplUbpQz+hirzRwEhgllkmUykVXheKoqSohKNZR7F+b2Xpopc42nY92cH5rFzfg4IuP8GgAhgEq1yUHdBhgKEMTIUwrMswsSUIgtBk8fVIIguIAZZWI+8crXWw+X+qUioOeJIqlIsr8s/lsvyFT8hcu4RdzXLZ43eCg50OcrTbUQojnb2hlvWV3Up1IKLbKCb2H8XonqMY2WOk+DoSBOGSwqdKQmudAFQ5FaOUigSs5ZLToEy8HLfYjp7hs9StfLtmKXsu/MCJ4J843nMfF8e5NiwDBBQH0i/wSq4ZNIaJAyIY1XMUocGhMm0kCMIlTUM1XIcBp8ul2QBLVQW3799En/904GxQMQxynSdABzCw+UBG9RvF1QOvJqJ7BIM7DZbdy4IgCOVoqE/FDi7STgNVzvXkNSsmz8l9kSrxo4OtNyF+lzN+6ASiIydyZfehNA9oXnfSCoIgNFEaqpJwR/nRBQBKqVggFiCgs2L4/su4rO113HZzNLdeM5ZWgRJyUxAEoSY0VCWRTekqKDvtqWinAEBrnQwkA0REROiM/2V4VzpBEIRLBL/6FsANVrAHaHYQimG8FgRBEHxEfSqJMnYHpVS8uaoJrXU6YDP3StiJxBwtCIIgCL7B15vpIoEojFFCiLm8dJa5Qc6+vDXd/BsOJCqlRpqfZ3prx7UgCILgGqW1rjpXIyIiIkJnZIhNQhAEwROUUpla64jy6Q3VJiEIgiA0AERJCIIgCG4RJSEIgiC4RZSEIAiC4BZREoIgCIJbREkIgiAIbhElIQiCILhFlIQgCILgFlESgiAIglua3I5rpdQ5YGd9y9GA6QicrG8hGjDSP5Uj/VM5jbl/+mitO5VPbKiuwmvDTldbywUDpVSG9I97pH8qR/qncppi/8h0kyAIguAWURKCIAiCW5qikpCYE5Uj/VM50j+VI/1TOU2uf5qc4VoQBEGoO5riSEIQBEGoIxrd6ialVAhGKFOABZVFq/Mkb1PB02tWSlkuhX6xU5N7QimVAmzQWs/2pmwNgZrcP0As0EFrneBd6eofD58/YUBEdfI2ZBrVSMKMeR0HLABOA5nmTVqrvE0FD/snSSmlgRylVI5SKtZ3ktYPNbknzDLRleVpKnjaP+ZDcCmQeokoCE9+X/EYIZkXAFZgr6lgGh9a60ZzADnlPqcBibXN21SO6l4zRozxNMBiHkmABkLq+xoaQv+Uy5MIZAPx9S1/Q+ofIMTsF0t9y93Q+sf8TelyaSlAbH1fQ02ORjOSUEpFYmhkZ9IoHfrVKG9TwcNrDgHitNY284gz06V/ypaJB2aZH23ekaxhUIP+ScF4QNq8KVdDoYb3j/M5C5BR95J5n8ZkkwjDGOI5Y8Po/NrkbSpU+5q11qlu6miUN3E18eieMKcGbFprm1LKu5I1DKrdP2bfhAFWpVQaxktHutPLRlPEk9+XTSmVDqQppezTcCla6yyvSuglGpOS6OAi7TTQvpZ5mwo1vmZzrjWrsd7E1cTT/onTl8A8uxOe9I/9DTkKiMFQEkuVUjRhReHR/aO1jlJKZWNMVwI02nup0Uw3VUJ57V5XeZsKlV6zaXh7EpjkE2kaHhX6x5wmSKsHWRoiru6fUIxRVoI5XZmFsYlsum9FaxC4/H2ZI6w4IBiYDSQqpZJ8KVhd0ZiURDYVtXZ7Ks4Tepq3qVDTa54DxFwCc8ue9E8SxlSBNleAhQD21WBNFU9/X+Ufjhu8IVQDotr9Y47M0Vqnm0o0AUNRNEol2piUhBVjXtCZUFy/8XmSt6ng8TWb6/8TtNZNWXnaqXb/aK1DtdbKfphlE8z/myqe/r7KL+dsT9O2aXnSPyOB8lO3G2is/VPfy6s8XYIGRDt9zsRcggfEA5HVydtUDw/7JwVj/X+YeUQ6n2+Khyf9U67cJbME1oP7J7tc3jS5f4zrN39P2eXKpjTW/mlMhmuAcIy5vZHm55m6dJpkhvk3vRp5myrV6h9zbtTdJrGm/Lbsyf1jt03YDbNxpmG2Ke+69vT3Nccpb6LW2tF3TZRq9Y/WOksplWCO1O2j9KTG2j/i4E8QBEFwS2OySQiCIAg+RpSEIAiC4BZREoIgCIJbREkIgiAIbhElIQiCILhFlIQgCILgFlESgiAIgltESQh1ilIqWill93uUZkbAS1NKZZvxGYRaoJRKMSMJWqqRN9bMX2lkPaWUxSlv44yeJngNURJCnaKNWBV2t8gJWus4rXUUhkfMRG+ESVVKJZpeN6uTt9EGVrL72gImVdN7wAIMdyuVuos368rA2IFvqUKGRtt/Qs1obG45hEaK1jpdKWXDcG1Q16Rh+BKqFKVUIsZD0xsyeBUznnSY9sAZozaC31TLPb7pSqIqGRpt/wk1R5SE4GscD3NzymQ6cFq7j5ZXBnPqpD1gtfvCceUTx1U+E1fxIzyWo7p4UreZ1/7mn6HLBoGKqA+ZXFDtmCzm9GIHjBFKXGP1XXSpI9NNgk9wmqZINj/HYsSyWGB+zjbnxiPNufE0pVSYOf8eb57LxHDBnA4kmOcd+c163OWze7qNMPPHVyFHvFIq05zKijXTc1zZVZzm83PMMpbK6nbTP9EYUczSMaZ+Usw3d/tDPQpob9p43Np2TJtQoilHGuWmmqohk72NHPNcrJnPZf9VIkcSkKqNWAqJlEZoExob9e2GVo6md2C4Stbm33iMB0QKEGKeDwFyypVxuOM28+dgBP+JNeuIBdKc8oc41ZcIZJr/u8yHMdeehOne2TyqkiPT/BzpVLe2t2umlXEBjRHLuMprLJduMeu1uOjDSPN8olk+BDcu783ri3ZRR2w1+12X+54Snb7HCv1Xyfcfbe8HJzly3OWXo2EfMpIQvIrWerY2wlzG6NL59EgqTltYMYK1AJwyy8ZprZO14Z47A4g0RxjxGA8pq3N+E5f5tGGctWFMsdjMz1XJcRrD9bN9WivZTA8Dx9t/iC47jWI32ldVtzPTMcKB2uwJ2phqslIaNTDbTLdqF0Zr801/unaaPnKqw051ZEqy96s2RgE2YIab/nPHk5SNVFcmgps5StPm30TTIC80UMQmIdQH4RjTGvYpiFMYb7DOkbvKGGi1YVgNx3gAPYmxUirO6cHtUb5qymEzD2ecP4+k3EPXSXFV5xrtWFyklW+rKiLKy+KC6sjkSomcwjPCgFlOn0Oc29Bazza/k9kA5tRYmC5rgxEaCKIkhPrABo431Wrh9BCJMT8nYiyrTa5JvprKUY5TuDcoe1K3FbAopSzl3tAtGNM71eE0EOKiDmebhCcyOctQbeO2k+3JWYYojKkqe54QKsaGvhRC6DZKZLpJqA+SMB6Kzg8OSxUbuSLKnc8G5nuY7xRmbGbTWFuVHBZcv+XbH7zJ5cs7Ue1rNKeIbDgZd818NjcjIFekm3XMcaqjvHG5OjJFOJ2LxWn6iYr954oo82+Yc75yU3L2c/apppgqpq+E+qS+jSJyNK0DY947DcPgmYaTIbVcvjDzfA7GlEcixgM5GuPtOceeZua3pyeZR3y59BwMA7fLfGbeEAylkYOx56AyOeLNtPKxnHPM/K7Kp1HRYFuhbjf9EWIvj2msL9enmWafuo21bbZn74tMp+vNpGz8ZVfXa6F0v0m22XeRLmQs038uZLDXmW3+jXWRJ9Hep+a1Ztb3fSuH+0PClwqCUGeYy4+dFym4ypMCzNKmDUIplaO1DvaVjIJnyHSTIAh1iaUaecKcFEQZo7bQ8BDDtSAIdUmlDgLNpbohpr3EhjH9FlVZGaF+ESUhCEJdYqvspDmCqNxJlNCgEJuEIAiC4BaxSQiCIAhuESUhCIIguEWUhCAIguAWURKCIAiCW0RJCIIgCG4RJSEIgiC45f8DijU3+zTachYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figureE2(rhoBs, mult_impact, mult_cumul, **opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Table 4 (IKC environment part)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RA</th>\n",
       "      <th>TA</th>\n",
       "      <th>TABU</th>\n",
       "      <th>HA-one</th>\n",
       "      <th>HA-two</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BB impact</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BB cumulative</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DF impact</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>5.6</td>\n",
       "      <td>6.9</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DF cumulative</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.5</td>\n",
       "      <td>16.6</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                RA   TA  TABU  HA-one  HA-two\n",
       "BB impact      1.0  1.0   1.0     1.0     1.0\n",
       "BB cumulative  1.0  1.0   1.0     1.0     1.0\n",
       "DF impact      1.0  1.9   5.6     6.9     3.6\n",
       "DF cumulative  1.0  1.0  15.5    16.6     2.7"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plots.table4(mult_impact, mult_cumul).round(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Testing analytical formulas\n",
    "First, proposition 4 says that we can write\n",
    "$$\n",
    "d\\mathbf{Y} = d\\mathbf{G} + \\mathcal{M}\\cdot\\mathbf{M}\\cdot (d\\mathbf{G}-d\\mathbf{T}) \\tag{30}\n",
    "$$\n",
    "We can easily test that this agrees with our results above, from equation (16), up to some numerical error caused by truncation of Jacobians. This error is extremely small except in the HA-two model—where it is still small, but the very high long-run persistence of spending out of the illiquid account leads to more error from truncation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "for m in curlyMs:\n",
    "    for i, (rhoB, dT) in enumerate(zip(rhoBs, dTs)):\n",
    "        dY = dG + curlyMs[m] @ (Ms[m] @ (dG - dT))    # equation (30), prop4\n",
    "        assert np.allclose(dY[:100], dYs[m][i][:100], atol=(1E-3 if m == 'HA-two' else 1E-9))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we have formulas characterizing $d\\mathbf{Y}$ for each of the analytical models.\n",
    "\n",
    "**RA model.** Proposition 5 states that the RA model has $d\\mathbf{Y} = d\\mathbf{G}$ regardless of persistence:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert all(np.allclose(dYs['RA'][i], dG) for i in range(NrhoB))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**TA model.** Proposition 6 states that the TA model has $d\\mathbf{Y} = d\\mathbf{G} + \\frac{\\mu}{1-\\mu}(d\\mathbf{G}-d\\mathbf{T})$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "mu = params['TA']['mu']\n",
    "assert all(np.allclose(dYs['TA'][i], dG + mu/(1-mu)*(dG - dTs[i])) for i in range(NrhoB))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**BU and TABU models.** Equation (31) in Proposition 7, defining the saver's MPC $m\\equiv 1-\\frac{\\lambda}{1+r}$ for convenience, states that for a TABU model\n",
    "$$\n",
    "dY_t = dG_t + \\frac{\\mu}{1-\\mu}(dG_t - dT_t) + (1+r)\\frac{m}{1-\\mu}\\left(\\lambda^{-1} - \\beta(1+r)\\right)\\sum_{s=0}^\\infty (\\beta(1+r))^s dB_{t+s}\n",
    "$$\n",
    "Writing this as a function, we have:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pdv_dB(dB, b):\n",
    "    # recursively take pdv of future dB using discount factor b\n",
    "    pdv = np.empty(len(dB))\n",
    "    pdv[-1] = dB[-1]\n",
    "    for t in reversed(range(T-1)):\n",
    "        pdv[t] = b*pdv[t+1] + dB[t]\n",
    "    return pdv\n",
    "\n",
    "def dY_TABU(dG, dT, dB, r, beta, mu, lamb):\n",
    "    m = 1 - lamb/(1+r) \n",
    "    return dG + mu/(1-mu)*(dG - dT) + (1+r)*m/(1-mu)*(1/lamb - beta*(1+r))*pdv_dB(dB, beta*(1+r))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now testing for the BU case:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "beta, mu, lamb = params['BU']['beta'], 0, params['BU']['lamb']\n",
    "assert all(np.allclose(dY_TABU(dG, dT, dB, r, beta, mu, lamb), dYs['BU'][i])\n",
    "                                    for i, (dT, dB) in enumerate(zip(dTs, dBs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Testing for the TABU case:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "beta, mu, lamb = params['TABU']['beta'], params['TABU']['mu'], params['TABU']['lamb']\n",
    "assert all(np.allclose(dY_TABU(dG, dT, dB, r, beta, mu, lamb), dYs['TABU'][i])\n",
    "                                    for i, (dT, dB) in enumerate(zip(dTs, dBs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**ZL model.** Equation (A.110) in Proposition 11 states that for a ZL model,\n",
    "$$\n",
    "dY_t = dG_t + \\frac{\\mu}{1-\\mu}(dG_t-dT_t) - \\frac{1-\\beta(1+r)}{1-\\mu}dB_t + (1+r)\\frac{1-\\beta\\lambda}{1-\\mu}(\\lambda^{-1}-1)\\sum_{s=0}^\\infty dB_{t+s}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "beta, mu, lamb = params['TABU']['beta'], params['TABU']['mu'], params['TABU']['lamb']\n",
    "assert all(np.allclose(dYs['ZL'][i], dG + mu/(1-mu)*(dG-dTs[i]) - (1-beta*(1+r))/(1-mu)*dBs[i]\n",
    "        + (1+r)*(1-beta*lamb)/(1-mu)*(1/lamb - 1)*pdv_dB(dBs[i], 1)) for i, (dT, dB) in enumerate(zip(dTs, dBs)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing the role of anticipation with cognitive discounting\n",
    "Now we create Figure 6(a) and Figure E.5, obtaining cumulative multipliers for our set of similar models that fit the iMPC data (TABU, HA-one, HA-two) as we dampen expectations by adjusting the cognitive discount factor $\\delta$.\n",
    "\n",
    "First, for this exercise we set $\\rho_B$ at a particular value, $\\rho_G$, and then vary $\\delta$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "rhoB = calibration.rhoG\n",
    "dB = Bplan(dG, rhoB)\n",
    "dT = Tplan(dG, dB, 1+r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we calculate $\\mathbf{M}$ and $\\mathcal{M}$ as we vary $\\delta$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "models = ['HA-one', 'TABU', 'HA-two']\n",
    "deltas = np.linspace(0, 1, 20)\n",
    "Ms_disc, curlyMs_disc = {}, {}\n",
    "for m in models:\n",
    "    Ms_disc[m], curlyMs_disc[m] = {}, {}\n",
    "    for i, delta in enumerate(deltas):\n",
    "        A, M = jac.cognitive_discounting(As[m], delta), jac.cognitive_discounting(Ms[m], delta)\n",
    "        Ms_disc[m][i], curlyMs_disc[m][i] = M, np.linalg.solve(A, K)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure 6(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then calculate cumulative multipliers for each model as we vary $\\delta$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "mult_disc = {}\n",
    "for m in models:\n",
    "    mult_disc[m] = np.empty_like(deltas)\n",
    "    for i, delta in enumerate(deltas):\n",
    "        dY = curlyMs_disc[m][i] @ (dG - Ms_disc[m][i] @ dT)\n",
    "        _, _, mult_disc[m][i] = compute_multipliers(dY, dG, r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figure6_E5(deltas, mult_disc,\n",
    "               title='(a) Cumulative multiplier with cognitive discounting',\n",
    "               xlabel=r'Cognitive discount factor $\\delta$', id='6_a', **opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure E.2\n",
    "We can also vary the multiplier $\\mathcal{M}$, which applies to gross income, and the direct effect of taxes $\\mathbf{M}d\\mathbf{T}$ separately, applying cognitive discounting to one but not the other. This is in figure E.2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "mult_only_taxes, mult_only_income = {}, {}\n",
    "for m in models:\n",
    "    mult_only_taxes[m], mult_only_income[m] = np.empty_like(deltas), np.empty_like(deltas)\n",
    "    for i, delta in enumerate(deltas):\n",
    "        # only apply cognitive discounting to M matrix applied to taxes\n",
    "        dY_only_taxes = curlyMs[m] @ (dG - Ms_disc[m][i] @ dT)\n",
    "\n",
    "        # only apply cognitive discounting to curlyM multiplier matrix, amplifying income\n",
    "        dY_only_income = curlyMs_disc[m][i] @ (dG - Ms[m] @ dT)\n",
    "\n",
    "        _, _, mult_only_taxes[m][i] = compute_multipliers(dY_only_taxes, dG, r)\n",
    "        _, _, mult_only_income[m][i] = compute_multipliers(dY_only_income, dG, r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figure6_E5(deltas, mult_only_taxes,\n",
    "               title='(a) Cognitive discounting of taxes, not income',\n",
    "               xlabel=r'Cognitive discount factor $\\delta$', id='E5_a', **opts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figure6_E5(deltas, mult_only_income,\n",
    "               title='(b) Cognitive discounting of income, not taxes',\n",
    "               xlabel=r'Cognitive discount factor $\\delta$', id='E5_b', **opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing the role of tail behavior with truncation\n",
    "Now we create Figure 6(b), obtaining cumulative multipliers for the same set of models as we \"truncate\" the $\\mathbf{M}$ spending response past some distance $T_0$ from the main diagonal (scaling up the remaining iMPCs to enforce budget balance)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "T0s = np.arange(10, 51, 2)\n",
    "mult_trunc = {}\n",
    "for m in models:\n",
    "    mult_trunc[m] = np.empty(len(T0s))\n",
    "    for i, T0 in enumerate(T0s):\n",
    "        M, A = jac.truncate_M(Ms[m], T0, T0, r)\n",
    "        dY = np.linalg.solve(A, K @ (dG - M @ dT))\n",
    "        _, _, mult_trunc[m][i] = compute_multipliers(dY, dG, r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure 6(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figure6_E5(T0s, mult_trunc,\n",
    "               title=r'(b) Cumulative multiplier with truncated $\\mathbf{M}$',\n",
    "               xlabel=r'Truncation date $T_0$', id='6_b', **opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Alternative: Lump-sum taxation at the margin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load a slightly modified version of the HA-one model that has a lump-sum transfer (calibrated to zero in steady state) built in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from models_heterogeneous import get_ha_one_lumpsum\n",
    "ha_one_lumpsum, ss_lumpsum = get_ha_one_lumpsum(params['HA-one'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Obtain $\\mathbf{M}^T$ matrix with respect to this transfer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "M_lumpsum = ha_one_lumpsum.jacobian(ss_lumpsum, inputs=['Tr'], outputs=['C', 'A'], T=T)['C', 'Tr']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What is \"partial equilibrium\" output effect $(\\mathbf{I} - \\mathbf{M})d\\mathbf{G}$ of a balanced-budget spending shock for our benchmark case, vs. the effect $(\\mathbf{I} - \\mathbf{M}^T)d\\mathbf{G}$ here? The difference is the \"redistribution\" effect $(\\mathbf{M}^T - \\mathbf{M})\\mathbf{G}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "dY_pe_bench = dG - Ms['HA-one'] @ dG\n",
    "dY_pe_lumpsum = dG - M_lumpsum @ dG\n",
    "dY_pe_redist = dY_pe_lumpsum - dY_pe_bench"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, what about the GE effects?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "dY_ge_bench = curlyMs['HA-one'] @ (dG - Ms['HA-one'] @ dG)\n",
    "dY_ge_lumpsum = curlyMs['HA-one'] @ (dG - M_lumpsum @ dG)\n",
    "dY_ge_redist = dY_ge_lumpsum - dY_ge_bench"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure E.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figureE1(dY_pe_bench, dY_pe_lumpsum, dY_pe_redist,\n",
    "               title='(a) Output: partial equilibrium', id='a', **opts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figureE1(dY_ge_bench, dY_ge_lumpsum, dY_ge_redist, yticks=[-0.5, 0, 0.5, 1],\n",
    "               title='(b) Output: general equilibrium', id='b', **opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PE to GE: fiscal policy, monetary policy, and deleveraging\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Need to load a slightly modified version of the HA-one household block:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "from models_heterogeneous import get_ha_one_con\n",
    "ha_one_con, ss_con = get_ha_one_con(params['HA-one'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then, in addition to our original $\\mathbf{M}$ matrix, which will be unchanged, we need the $\\mathbf{M}^r$ matrix in response to real interest rates, and also the response to a \"deleveraging\" shock to the borrowing constraint."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "jacs = ha_one_con.jacobian(ss_con, inputs=['r', 'a_con'], outputs=['C'], T=T)\n",
    "Mr, Mcon = jacs['C', 'r'], jacs['C', 'a_con']\n",
    "curlyM, M = curlyMs['HA-one'], Ms['HA-one']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Deficit-financed spending shock.**\n",
    "The parameters for this shock are a bit different from our previous exercise, with $\\rho_G=0.8$ and $\\rho_B=0.5$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "dG = 0.8**np.arange(T)\n",
    "dB = Bplan(dG, 0.5)\n",
    "dT = Tplan(dG, dB, 1+r)\n",
    "\n",
    "dY_pe_deficit = dG - M @ dT\n",
    "dY_ge_deficit = curlyM @ dY_pe_deficit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Monetary policy shock.** This shock is $dr_t=0.8^t$, but we need to translate to the ex-post timing for $r$ used by our blocks, in which the ex-post interest rate at date 0 is unchanged:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "dr = np.zeros(T)\n",
    "dr[1:] = 0.8**np.arange(T-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We assume that the government follows a balanced-budget rule, immediately raising taxes to pay interest on the debt:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "dT = ss_con['A']*dr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can solve for the PE and GE effects:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "dY_pe_monetary = Mr @ dr - M @ dT\n",
    "dY_ge_monetary = curlyM @ dY_pe_monetary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Deleveraging shock.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "dacon = 0.8**np.arange(T)\n",
    "dY_pe_delev = Mcon @ dacon\n",
    "dY_ge_delev = curlyM @ dY_pe_delev"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure A.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figureA2(dY_pe_deficit, dY_pe_monetary, dY_pe_delev,\n",
    "               title=r'(a) Partial equilibrium $\\partial \\mathbf{Y}$', id='a', **opts) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x324 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plots.figureA2(dY_ge_deficit, dY_ge_monetary, dY_ge_delev,\n",
    "               title=r'(b) General equilibrium $\\mathbf{Y}$', id='b', **opts)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
